Simulated training environments based upon fixated objects in specified regions

Abstract

Objects associated with fixation regions are used to support training tasks that are characterized by operation within a dynamic 3D environment, problem-solving that involves user multi-tasking, fast decisions, heavy workloads, potential for unexpected events, and the need for high-performance skills. The invention is ideally suited to measure the nuances associated with maintaining situation awareness in such tasks where dynamic 3D environments that support problem solving with high cognitive fidelity have already been developed. Potential training application areas include urban warfighting, night vision goggle use, aircraft piloting, helicopter operation, remote control of vehicles and robots, night driving, air traffic control, and quarterback decision-making.

Description

REFERENCE TO RELATED APPLICATION [0001] This application claims priority from U.S. Provisional Patent Application Ser. Nos. 60 / 712,197, Aug. 29, 2005 and 60 / 740,596, filed Nov. 29, 2005. This application is also a continuation-in-part of U.S. patent application Ser. No. 11 / 070,038 filed Mar. 2, 2005, which claims priority from U.S. Provisional Patent Application Ser. No. 60 / 549,489, filed Mar. 2, 2004. The entire content of all of which are incorporated herein by reference.FIELD OF THE INVENTION [0002] This invention relates to a system and method for calculating eye events (or foveated-object events) that correspond to visual fixations on objects within a dynamic field of view, and more particularly, to such a system in which fixation regions are registered to an internal computer model that represents the field of view to determine the fixated objects within the model, an eye event that corresponds to those objects is constructed and placed in the computer environment, and the res...

AI Technical Summary

Benefits of technology

[0011] The present invention resides in a novel approach to calculating the objects associated with eye fixations. The benefits of this approach are significant. The invention is well-suited to support training tasks that are characterized by operation within a dynamic 3 D environment, problem-solving that involves user multitasking, short decision time periods, heavy workloads, potential for unexpected events, and the need for high-performance skills. It is ideally suited to measure the nuances associated with maintaining situation awareness in such problems where dynamic 3 D environments that support problem solving with high cognitive fidelity have already been developed. Potential training application areas include urban warfighting, night vision goggle use, aircraft pilot, helicopter operation, remote control of vehicles and robots, night driving, sports decision making, air traffic control, personnel selection, attention management for situation awareness, soldier skills, vigilance methods, aged performance, attention management rehabilitation, and cognitive rehabilitation.

Problems solved by technology

Despite significant progress, widespread application of the technology has failed to become a reality.

In part, this is due to the remaining high cost of eyetracker devices.

An additional barrier, however, is the difficulty in mapping the sequence of fixation points produced by an eyetracker to objects that are present in the individual's field of view.

Although this is adequate for some research applications, it is simply too costly and too cumbersome for widespread use.

Attempts at automating the mapping of points to objects have proven difficult.

Although successes have been developed using approaches from both of these classes, a general solution to the point-to-object problem still remains unsolved.

Despite extensive work, general-purpose, high-performance segmentation algorithms have proven elusive.

Current segmentation algorithms often require custom development and remain error prone.

The more general problem of mapping fixation regions to objects has received limited attention in the literature.

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